johannawawi/fine-tuning-javanese-sentiment-analysist-3-class2

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results

This model is a fine-tuned version of azizp128/javanese-sentiment-analysis-indobert on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.5921
• —Accuracy : 0.9033
• —F1 Macro : 0.9029
• —F1 Weighted : 0.9029
• —Precision Macro : 0.9052
• —Recall Macro : 0.9032
• —Precision Weighted : 0.9051
• —Recall Weighted : 0.9033

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 6e-06
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
• —lrschedulertype: linear
• —num_epochs: 10

Training results

Framework versions

• —Transformers 4.51.3
• —Pytorch 2.6.0+cu124
• —Datasets 3.5.1
• —Tokenizers 0.21.1